remaining med value features

backend/nodes/cross_correlate.py

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+from __future__ import annotations
+
+import numpy as np
+
+from backend.data_types import DataField
+from backend.node_registry import register_node
+
+
+@register_node(display_name="Cross-Correlate")
+class CrossCorrelate:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field_a": ("DATA_FIELD",),
+                "field_b": ("DATA_FIELD",),
+                "mode": (["full", "same", "valid"], {"default": "same"}),
+                "normalize": ("BOOLEAN", {"default": True}),
+            }
+        }
+
+    OUTPUTS = (
+        ('DATA_FIELD', 'correlation'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Compute 2D cross-correlation between two fields. The correlation peak indicates "
+        "the offset where the two fields best match. Useful for drift measurement and feature "
+        "alignment. Equivalent to Gwyddion crosscor.c."
+    )
+
+    def process(
+        self,
+        field_a: DataField,
+        field_b: DataField,
+        mode: str,
+        normalize: bool,
+    ) -> tuple:
+        from scipy.signal import fftconvolve
+
+        a = field_a.data - field_a.data.mean()
+        b = field_b.data - field_b.data.mean()
+
+        # Cross-correlation via FFT: correlate(a,b) = ifft(fft(a) * conj(fft(b)))
+        # Achieved by convolving a with the flipped b
+        corr = fftconvolve(a, b[::-1, ::-1], mode=mode)
+
+        if normalize:
+            denom = np.sqrt((a ** 2).sum() * (b ** 2).sum())
+            if denom > 0:
+                corr = corr / denom
+
+        if mode == "same":
+            # Output is the same shape as field_a — reuse its physical dimensions
+            return (field_a.replace(data=corr),)
+
+        # For "full" mode: output shape is (Na+Nb-1, Ma+Mb-1)
+        # Scale physical dimensions proportionally
+        na, ma = field_a.data.shape
+        nb, mb = field_b.data.shape
+        out_y, out_x = corr.shape
+
+        # Physical size per pixel stays the same as field_a; total physical size scales
+        new_xreal = field_a.xreal * out_x / ma if ma > 0 else field_a.xreal
+        new_yreal = field_a.yreal * out_y / na if na > 0 else field_a.yreal
+
+        return (field_a.replace(data=corr, xreal=new_xreal, yreal=new_yreal),)